Cloud Version Available: A cloud version of the AI Reviewer is available at https://www.rigorous.company/. Simply upload your manuscript, provide context on target journal and review focus, and receive a comprehensive PDF report via email within 1-2 working days. We'll provide feedback free of charge — however, we would greatly appreciate your feedback in return via this short form to help us improve the AI Reviewer.
This repository is intended for tools that make the creation, evaluation, and distribution of scientific knowledge more transparent, cheaper, faster, and better. Let's build this future together!
- Agent1_Peer_Review: Multiagent AI review system for comprehensive manuscript analysis, detailed feedback, and professional PDF report generation.
- Agent2_Outlet_Fit: (In Development) Tool for evaluating manuscript fit with target journals/conferences.
- Agent1_Peer_Review: ✅ MVP Ready for use!
- Comprehensive manuscript analysis with specialized agents
- Detailed feedback on sections, scientific rigor, and writing quality (including quality control loops)
- JSON output with actionable recommendations
- PDF report generation
- 📄 Detailed Documentation
- Please provide feedback via this short feedback form to help us improve the system.
- Agent2_Outlet_Fit: 🚧 In Development
- Core functionality being implemented
- Integration with Agent1_Peer_Review in progress
- Testing and validation ongoing
- 🛠️ Development Plan
- Python 3.7+
- OpenAI API key (the system can be adapted to alternative LLMs, including locally hosted ones)
- PDF manuscripts to analyze
- Dependencies listed in each tool's requirements.txt
Contributions are welcome! Please feel free to submit a Pull Request.
If you use the Rigorous AI Reviewer in your research or project, please cite:
@software{rigorous_ai_reviewer2025,
author = {Jakob, Robert and O'Sullivan, Kevin},
title = {Rigorous AI Reviewer: Enabling AI for Scientific Manuscript Analysis},
year = {2025},
publisher = {GitHub},
url = {https://github.com/robertjakob/rigorous}
}
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